21st EANN 2020, 5 -7 June 2020, Greece

Eye Movement Data Analysis

Olga Georgieva, Nadejda Bocheva, Bilyana Genova, Miroslava Stefanova

Abstract:

  The aim of the present study is to investigate the separation abilities of three statistical parameters for grouping participants in the visual-motor experiment by their age and gender. These parameters represent different characteristics of the decision-making process and were determined by applying the hierar-chical drift diffusion model to the response time and accuracy of the exper-imental data. The objective function cluster analysis was applied to ex-plore distinct data spaces formed by the parameters’ data. The ability for grouping is assessed and interpreted according to the differences in the sub-jects’ capabilities to perform the visuo-motor task. The study compares the conclusions based by drift-diffusion model using Bayesian parameter esti-mation with those based on the cluster analysis in terms of ability to distin-guish the performance of different age groups. The investigation of gender effects are uniquely investigated by cluster analysis technique.  

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